code: def create_backend(
      self, project: ProjectModel, config: TensorDockConfigInfoWithCreds
  ) -> BackendModel:
      if config.regions is None:
          config.regions = REGIONS
      return BackendModel(
          project_id=project.id,
          type=self.TYPE.value,
          config=TensorDockStoredConfig(
              **TensorDockConfigInfo.parse_obj(config).dict()
          ).json(),
          auth=TensorDockCreds.parse_obj(config.creds).json(),
      )
  
file_path: dstack/src/dstack/_internal/server/services/backends/configurators/tensordock.py
imports: import json
  from typing import List
  from dstack._internal.core.backends.tensordock import TensorDockBackend, api_client
  from dstack._internal.core.backends.tensordock.config import TensorDockConfig
  from dstack._internal.core.models.backends.base import BackendType, ConfigElementValue, ConfigMultiElement
  from dstack._internal.core.models.backends.tensordock import AnyTensorDockConfigInfo, TensorDockConfigInfo, TensorDockConfigInfoWithCreds, TensorDockConfigInfoWithCredsPartial, TensorDockConfigValues, TensorDockCreds, TensorDockStoredConfig
  from dstack._internal.server.models import BackendModel, ProjectModel
  from dstack._internal.server.services.backends.configurators.base import Configurator, raise_invalid_credentials_error
label_desc: Use image node_id 3 for calling the TensorDockConfigurator obj's underlying member method code with example usage: obj.create_backend(project, config) and returns: BackendModel